qFit-ligand Reveals Widespread Conformational Heterogeneity of Drug-Like Molecules in X‑Ray Electron Density Maps
Proteins and ligands sample a conformational ensemble that governs molecular recognition, activity, and dissociation. In structure-based drug design, access to this conformational ensemble is critical to understand the balance between entropy and enthalpy in lead optimization. However, ligand confor...
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Veröffentlicht in: | Journal of medicinal chemistry 2018-12, Vol.61 (24), p.11183-11198 |
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creator | van Zundert, Gydo C. P Hudson, Brandi M de Oliveira, Saulo H. P Keedy, Daniel A Fonseca, Rasmus Heliou, Amelie Suresh, Pooja Borrelli, Kenneth Day, Tyler Fraser, James S van den Bedem, Henry |
description | Proteins and ligands sample a conformational ensemble that governs molecular recognition, activity, and dissociation. In structure-based drug design, access to this conformational ensemble is critical to understand the balance between entropy and enthalpy in lead optimization. However, ligand conformational heterogeneity is currently severely underreported in crystal structures in the Protein Data Bank, owing in part to a lack of automated and unbiased procedures to model an ensemble of protein–ligand states into X-ray data. Here, we designed a computational method, qFit-ligand, to automatically resolve conformationally averaged ligand heterogeneity in crystal structures, and applied it to a large set of protein receptor–ligand complexes. In an analysis of the cancer related BRD4 domain, we found that up to 29% of protein crystal structures bound with drug-like molecules present evidence of unmodeled, averaged, relatively isoenergetic conformations in ligand–receptor interactions. In many retrospective cases, these alternate conformations were adventitiously exploited to guide compound design, resulting in improved potency or selectivity. Combining qFit-ligand with high-throughput screening or multitemperature crystallography could therefore augment the structure-based drug design toolbox. |
doi_str_mv | 10.1021/acs.jmedchem.8b01292 |
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P ; Hudson, Brandi M ; de Oliveira, Saulo H. P ; Keedy, Daniel A ; Fonseca, Rasmus ; Heliou, Amelie ; Suresh, Pooja ; Borrelli, Kenneth ; Day, Tyler ; Fraser, James S ; van den Bedem, Henry</creator><creatorcontrib>van Zundert, Gydo C. P ; Hudson, Brandi M ; de Oliveira, Saulo H. P ; Keedy, Daniel A ; Fonseca, Rasmus ; Heliou, Amelie ; Suresh, Pooja ; Borrelli, Kenneth ; Day, Tyler ; Fraser, James S ; van den Bedem, Henry ; SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States)</creatorcontrib><description>Proteins and ligands sample a conformational ensemble that governs molecular recognition, activity, and dissociation. In structure-based drug design, access to this conformational ensemble is critical to understand the balance between entropy and enthalpy in lead optimization. However, ligand conformational heterogeneity is currently severely underreported in crystal structures in the Protein Data Bank, owing in part to a lack of automated and unbiased procedures to model an ensemble of protein–ligand states into X-ray data. Here, we designed a computational method, qFit-ligand, to automatically resolve conformationally averaged ligand heterogeneity in crystal structures, and applied it to a large set of protein receptor–ligand complexes. In an analysis of the cancer related BRD4 domain, we found that up to 29% of protein crystal structures bound with drug-like molecules present evidence of unmodeled, averaged, relatively isoenergetic conformations in ligand–receptor interactions. In many retrospective cases, these alternate conformations were adventitiously exploited to guide compound design, resulting in improved potency or selectivity. 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P</creatorcontrib><creatorcontrib>Hudson, Brandi M</creatorcontrib><creatorcontrib>de Oliveira, Saulo H. P</creatorcontrib><creatorcontrib>Keedy, Daniel A</creatorcontrib><creatorcontrib>Fonseca, Rasmus</creatorcontrib><creatorcontrib>Heliou, Amelie</creatorcontrib><creatorcontrib>Suresh, Pooja</creatorcontrib><creatorcontrib>Borrelli, Kenneth</creatorcontrib><creatorcontrib>Day, Tyler</creatorcontrib><creatorcontrib>Fraser, James S</creatorcontrib><creatorcontrib>van den Bedem, Henry</creatorcontrib><creatorcontrib>SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States)</creatorcontrib><title>qFit-ligand Reveals Widespread Conformational Heterogeneity of Drug-Like Molecules in X‑Ray Electron Density Maps</title><title>Journal of medicinal chemistry</title><addtitle>J. Med. Chem</addtitle><description>Proteins and ligands sample a conformational ensemble that governs molecular recognition, activity, and dissociation. In structure-based drug design, access to this conformational ensemble is critical to understand the balance between entropy and enthalpy in lead optimization. However, ligand conformational heterogeneity is currently severely underreported in crystal structures in the Protein Data Bank, owing in part to a lack of automated and unbiased procedures to model an ensemble of protein–ligand states into X-ray data. Here, we designed a computational method, qFit-ligand, to automatically resolve conformationally averaged ligand heterogeneity in crystal structures, and applied it to a large set of protein receptor–ligand complexes. In an analysis of the cancer related BRD4 domain, we found that up to 29% of protein crystal structures bound with drug-like molecules present evidence of unmodeled, averaged, relatively isoenergetic conformations in ligand–receptor interactions. In many retrospective cases, these alternate conformations were adventitiously exploited to guide compound design, resulting in improved potency or selectivity. 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P ; Hudson, Brandi M ; de Oliveira, Saulo H. 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P</creatorcontrib><creatorcontrib>Keedy, Daniel A</creatorcontrib><creatorcontrib>Fonseca, Rasmus</creatorcontrib><creatorcontrib>Heliou, Amelie</creatorcontrib><creatorcontrib>Suresh, Pooja</creatorcontrib><creatorcontrib>Borrelli, Kenneth</creatorcontrib><creatorcontrib>Day, Tyler</creatorcontrib><creatorcontrib>Fraser, James S</creatorcontrib><creatorcontrib>van den Bedem, Henry</creatorcontrib><creatorcontrib>SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States)</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>OSTI.GOV - Hybrid</collection><collection>OSTI.GOV</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Journal of medicinal chemistry</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>van Zundert, Gydo C. P</au><au>Hudson, Brandi M</au><au>de Oliveira, Saulo H. P</au><au>Keedy, Daniel A</au><au>Fonseca, Rasmus</au><au>Heliou, Amelie</au><au>Suresh, Pooja</au><au>Borrelli, Kenneth</au><au>Day, Tyler</au><au>Fraser, James S</au><au>van den Bedem, Henry</au><aucorp>SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States)</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>qFit-ligand Reveals Widespread Conformational Heterogeneity of Drug-Like Molecules in X‑Ray Electron Density Maps</atitle><jtitle>Journal of medicinal chemistry</jtitle><addtitle>J. Med. Chem</addtitle><date>2018-12-27</date><risdate>2018</risdate><volume>61</volume><issue>24</issue><spage>11183</spage><epage>11198</epage><pages>11183-11198</pages><issn>0022-2623</issn><eissn>1520-4804</eissn><abstract>Proteins and ligands sample a conformational ensemble that governs molecular recognition, activity, and dissociation. In structure-based drug design, access to this conformational ensemble is critical to understand the balance between entropy and enthalpy in lead optimization. However, ligand conformational heterogeneity is currently severely underreported in crystal structures in the Protein Data Bank, owing in part to a lack of automated and unbiased procedures to model an ensemble of protein–ligand states into X-ray data. Here, we designed a computational method, qFit-ligand, to automatically resolve conformationally averaged ligand heterogeneity in crystal structures, and applied it to a large set of protein receptor–ligand complexes. In an analysis of the cancer related BRD4 domain, we found that up to 29% of protein crystal structures bound with drug-like molecules present evidence of unmodeled, averaged, relatively isoenergetic conformations in ligand–receptor interactions. In many retrospective cases, these alternate conformations were adventitiously exploited to guide compound design, resulting in improved potency or selectivity. Combining qFit-ligand with high-throughput screening or multitemperature crystallography could therefore augment the structure-based drug design toolbox.</abstract><cop>United States</cop><pub>American Chemical Society</pub><pmid>30457858</pmid><doi>10.1021/acs.jmedchem.8b01292</doi><tpages>16</tpages><orcidid>https://orcid.org/0000-0003-2288-9157</orcidid><orcidid>https://orcid.org/0000-0003-2358-841X</orcidid><orcidid>https://orcid.org/000000032358841X</orcidid><orcidid>https://orcid.org/0000000322889157</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Amyloid Precursor Protein Secretases - antagonists & inhibitors Amyloid Precursor Protein Secretases - chemistry Amyloid Precursor Protein Secretases - metabolism Aspartic Acid Endopeptidases - antagonists & inhibitors Aspartic Acid Endopeptidases - chemistry Aspartic Acid Endopeptidases - metabolism Bioinformatics Calibration Cell Cycle Proteins Computational Biology - methods Computer Science Crystallography, X-Ray Databases, Protein Drug Design Electrons High-Throughput Screening Assays - methods INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY Ligands Models, Molecular Nuclear Proteins - chemistry Protein Domains Proteins - chemistry Proteins - metabolism Transcription Factors - chemistry |
title | qFit-ligand Reveals Widespread Conformational Heterogeneity of Drug-Like Molecules in X‑Ray Electron Density Maps |
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